A first AI initiative should be chosen like an operating change: around a defined task, accountable owner, trusted inputs, and a result that can be measured.
Guides for governing AI delivery
Retrieval quality is a knowledge-management problem before it is a model problem: sources need ownership, permissions, freshness controls, and a way to show users where an answer came from.
The safest automation is explicit about what it prepares, what it recommends, what it may execute, and when a person must decide.
An AI workflow should coordinate established applications without becoming an ungoverned shadow database or bypassing the approvals that make the operation reliable.
A demonstration proves possibility. A release decision needs representative tasks, known failure cases, quality thresholds, and a process to inspect what went wrong.
A pilot becomes a production capability only when it has an owner, support model, controls, measurement, and a deliberate decision to expand, hold, or stop.
Start with your delivery question
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